3D mapping of a scene by structured light triangulation comprises illuminating the scene with a light pattern and observing the illuminated scene with a camera whose optical axis is offset from the illumination source. If a given ray from the illumination intersects a reflective object, an image of this ray will by formed on the camera. The location of the image of this ray together with knowledge about the exact geometry of illumination-imaging setup allows the determination of the relative position of the intersection between the light ray and the object. This supposes that one knows which ray of the structured light pattern intersected the object. Finding the ray of the pattern, which corresponds to a point in the image, is often called the correspondence problem.
There are many strategies to solve the correspondence problem which, according to Salvi et al. (J. Salvi et al., Pattern codification strategies in structured light systems, Pattern Recognition 37 (2004) 827-849), can be categorized as follows:                Time-multiplexing        Direct codification        Spatial neighbourhood        
The time-multiplexing strategy comprises temporally coding the structured light pattern. A sequence of different patterns is projected and imaged one after the other. The 3D-map can be constructed by analyzing the complete sequence of images.
In the direct codification strategy, the correspondence problem is solved by coding the ray itself in a unique manner, mostly by colour (wavelength). This strategy thus requires the acquisition of a reference frame, since the scene is not uniform in spectral reflectivity. Furthermore the optical sub-system becomes quite complex. A broad-spectrum light has to be emitted and the imaging device needs colour (wavelength) measurement ability.
The spatial neighbourhood strategy solves the correspondence problem by coding the neighbourhood of a ray in a unique manner. By observing the image of the ray as well as the neighbourhood of this image, the ray can be identified. One particularly interesting implementation of this strategy involves a structured light pattern formed by a pseudo-random noise pattern of dots. According to the current state of the art, this pattern is created by processing the output of a laser with diffractive optical components (computer generated holograms for example). In order to make such a diffractive structured light triangulation robust with respect to sunlight, one has to make sure that there is sufficient contrast of the active illumination with respect to background light to discern the structured light pattern in the image frame captured by the video camera. There are certain parameters of the system, which can be optimized, such as the spectral range in which the camera is sensitive, however ultimately the only solution is to increase the intensity of the pattern. This can be obtained by increasing the power of the single laser or by combining the output from more than one laser by some beam-combining techniques. The first approach is limited, with current single emitter laser devices one can not reach an intensity which is sufficient to be robust with respect to sunlight. The second approach leads to a substantially increased complexity of the optical sub-system.